The human brain has a remarkable ability to flexibly allocate cognitive resources to meet task demands. Cognitive control machinery must maintain clear representation of current context (task demands), outcomes of prior choices, and control options for resolving conflict and adapting upcoming behavioral choices. Deficiencies in any of these operations can contribute to neuropsychiatric dysfunction. Research to date identifies a network of areas, including the dACC, as essential to cognitive control. However, key aspects of cognitive control, including how network components interact, and how they represent and manage conflict, remain controversial. On a technical level, the wide gap between methods used in human and monkey studies raises a host of uncertainties, including the possibility of substantial interspecies differences in cognitive control machinery. We identify and target two major impediments to progress: 1) lack of a robust, yet specific conceptual framework that can integrate disparate empirical findings; and 2) lack of high quality human data spanning the scale from single neuron spikes to population activity. We begin with an integrative conceptual model. The expected value of control (EVC) theory has recently been advanced to explain the role of the dACC in cognitive control. According to this model, the dACC weighs the expected benefit of successfully completing a control-demanding task against the cost required to do so. Based on this calculation, it generates a signal that specifies which (if any) task to perform, and how much control to allocate to the task. Specifically, the EVC model predicts that the dACC should perform the key functions mentioned at the outset: current context monitoring, outcome monitoring, and control signal specification. We test these functions with methods that effectively bridge the gap between single neuron activity in monkeys and noninvasive population measures in humans. We propose a series of experiments using functional imaging and intracranial electrophysiology methods in humans. Subjects will be patients with medically intractable epilepsy scheduled for intracranial electrode implantation for seizure monitoring. Prior to electrode implantation, they will undergo high-resolution fMRI. While implanted, they will perform behavioral tasks designed to test hypotheses regarding the role of the dACC as predicted by EVC theory. We will collect simultaneous single-unit and LFP recordings from dACC and LFPs from lateral PFC. Our broad goal is to validate a comprehensive theory of cognitive control using multi-modality human recordings. We do so by testing 3 Specific Aims aligned with the 3 proposed dACC functions mentioned above. In Specific Aim 1, we clarify the current context monitoring function of the dACC. We test hypotheses that the dACC encodes pure conflict signals, and that these neurons phase-lock to theta rhythms to coordinate dACC communication with other control-related regions. In Specific Aim 2, we define the outcome monitoring function of the dACC. We test hypotheses that human dACC neurons encode reward prediction errors (RPEs) and that these neurons entrain to theta oscillations to generate error- and feedback-related theta signals that can be observed on mid-frontal scalp EEG. Using information transfer analyses, we further hypothesize that RPE information travels from dACC to lateral PFC using theta-range oscillations. In Specific Aim 3, we establish evidence for a control specification function of the dACC. We test hypotheses investigating control signal targeting and intensity specification. Many neuropsychiatric disorders are attributable to the inability to ascribe appropriate value to contextual stimuli, attend to relevant features while ignoring irrelevant ones, and sequentially increase or decrease reward contingencies of actions based on feedback. Examples of disorders of this process include mood/anxiety disorders (OCD, depression, affective aspects of chronic pain), addiction, attention deficit disorders, and psychoses. A clearer appreciation of the neurophysiology of human cognitive control will be essential for the successful understanding and treatment of these behavioral disorders.